The article outlines the theoretical and practical foundations of a medical system designed for melanoma diagnostics. Each year, the mortality rate from melanoma increases, necessitating that medical institutions implement measures for the prevention and diagnosis of this disease. To make accurate diagnoses, doctors must analyze a substantial amount of data, which increases cognitive load and the likelihood of medical errors. Various medical systems are employed to reduce this cognitive load. These systems facilitate data collection, analysis, and support for medical decision-making. Each decision requires verification and must be backed by factual evidence. The proposed melanoma diagnostic system leverages Semantic Web technologies to enhance the explainability and interpretability of the inferred decisions. The article presents a knowledge model for the system and details the inference mechanism for the implementation of decision support. In addition, it thoroughly describes an illustrative example of the system’s operation.